Nothing
themis: Extra Recipes Steps for Dealing with Unbalanced Data
A dataset with an uneven number of cases in each class is said to be unbalanced. Many models produce a subpar performance on unbalanced datasets. A dataset can be balanced by increasing the number of minority cases using SMOTE 2011 <doi:10.48550/arXiv.1106.1813>, BorderlineSMOTE 2005 <doi:10.1007/11538059_91> and ADASYN 2008. Or by decreasing the number of majority cases using NearMiss 2003 <https://www.site.uottawa.ca/~nat/Workshop2003/jzhang.pdf> or Tomek link removal 1976.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Emil Hvitfeldt [aut, cre] (ORCID: <https://orcid.org/0000-0002-0679-1945>), Posit Software, PBC [cph, fnd] (ROR: <https://ror.org/03wc8by49>) |
| Maintainer | Emil Hvitfeldt <emil.hvitfeldt@posit.co> |
| License | MIT + file LICENSE |
| Version | 1.1.0 |
| URL | https://github.com/tidymodels/themis https://themis.tidymodels.org |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the themis package in your browser
Any scripts or data that you put into this service are public.
